The number of prediction models for suicide-related outcomes has grown substantially in recent years. These models aim to assist in stratifying risk, improve clinical decision-making, and facilitate a personalised medicine approach to the prevention of suicidal behaviour. However, there are contrasting views as to whether prediction models have potential to inform and improve assessment of suicide risk. In this perspective, we discuss common misconceptions that characterise criticisms of suicide risk prediction research. First, we discuss the limitations of a classification approach to risk assessment (eg, categorising individuals as low-risk vs high-risk), and highlight the benefits of probability estimation. Second, we argue that the preoccupation with classification measures (such as positive predictive value) when assessing a model's predictive performance is inappropriate, and discuss the importance of clinical context in determining the most appropriate risk threshold for a given model. Third, we highlight that adequate discriminative ability for a prediction model depends on the clinical area, and emphasise the importance of calibration, which is almost entirely overlooked in the suicide risk prediction literature. Finally, we point out that conclusions about the clinical utility and health-economic value of suicide prediction models should be based on appropriate measures (such as net benefit and decision-analytic modelling), and highlight the role of impact assessment studies. We conclude that the discussion around using suicide prediction models and risk assessment tools requires more nuance and statistical expertise, and that guidelines and suicide prevention strategies should be informed by the new and higher quality evidence in the field.

中文翻译：

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自杀风险评估工具和预测模型：新证据、方法创新、过时的批评。


近年来，自杀相关结果的预测模型数量大幅增加。这些模型旨在协助风险分层、改善临床决策并促进个性化医疗方法来预防自杀行为。然而，对于预测模型是否有可能为自杀风险的评估提供信息和改进，存在不同的观点。从这个角度来看，我们讨论了对自杀风险预测研究的批评的常见误解。首先，我们讨论风险评估分类方法的局限性（例如，将个体分类为低风险与高风险），并强调概率估计的好处。其次，我们认为在评估模型的预测性能时专注于分类测量（例如阳性预测值）是不合适的，并讨论了临床背景在确定给定模型最合适的风险阈值方面的重要性。第三，我们强调预测模型的足够辨别能力取决于临床领域，并强调校准的重要性，而这一点在自杀风险预测文献中几乎完全被忽视。最后，我们指出有关自杀预测模型的临床效用和健康经济价值的结论应基于适当的措施（例如净效益和决策分析模型），并强调影响评估研究的作用。我们的结论是，围绕使用自杀预测模型和风险评估工具的讨论需要更多的细微差别和统计专业知识，并且指南和自杀预防策略应以该领域新的、更高质量的证据为依据。